Add AI Resume Upload & Automatic Parsing feature

server.ts

@@ -223,6 +223,105 @@ Extract the following fields accurately and output JSON:
   }
 });
 
+// API 2B: Parse Master Resume Text / Document into User Profile
+app.post("/api/gemini/parse-resume", async (req, res) => {
+  try {
+    const { resumeText, llmConfig } = req.body;
+
+    if (!resumeText || typeof resumeText !== 'string' || resumeText.trim().length === 0) {
+      return res.status(400).json({ success: false, error: "Resume text content is required." });
+    }
+
+    const prompt = `Analyze the following resume text and extract all candidate information into structured JSON:
+
+Resume Content:
+${resumeText}
+
+Extract the following fields accurately:
+- fullName: Full Name of candidate
+- email: Email address
+- phone: Phone number
+- location: City, State or location preference
+- linkedinUrl: LinkedIn profile URL if found
+- githubUrl: GitHub profile URL if found
+- portfolioUrl: Personal website/portfolio URL if found
+- summary: Professional summary or objective paragraph
+- skills: Array of technical & soft skills
+- experience: Array of work experience objects, each with:
+    - id: unique string
+    - title: Job title
+    - company: Company name
+    - period: Date range (e.g. 2022 - Present)
+    - bullets: Array of accomplishment bullet points
+- education: Array of education objects, each with:
+    - degree: Degree title
+    - institution: School or University name
+    - year: Graduation year`;
+
+    const schema = {
+      type: Type.OBJECT,
+      properties: {
+        fullName: { type: Type.STRING },
+        email: { type: Type.STRING },
+        phone: { type: Type.STRING },
+        location: { type: Type.STRING },
+        linkedinUrl: { type: Type.STRING },
+        githubUrl: { type: Type.STRING },
+        portfolioUrl: { type: Type.STRING },
+        summary: { type: Type.STRING },
+        skills: {
+          type: Type.ARRAY,
+          items: { type: Type.STRING }
+        },
+        experience: {
+          type: Type.ARRAY,
+          items: {
+            type: Type.OBJECT,
+            properties: {
+              id: { type: Type.STRING },
+              title: { type: Type.STRING },
+              company: { type: Type.STRING },
+              period: { type: Type.STRING },
+              bullets: {
+                type: Type.ARRAY,
+                items: { type: Type.STRING }
+              }
+            }
+          }
+        },
+        education: {
+          type: Type.ARRAY,
+          items: {
+            type: Type.OBJECT,
+            properties: {
+              degree: { type: Type.STRING },
+              institution: { type: Type.STRING },
+              year: { type: Type.STRING }
+            }
+          }
+        }
+      },
+      required: ["fullName", "skills", "experience"]
+    };
+
+    const { text, providerUsed } = await generateTextWithLLMFallback(prompt, schema, llmConfig);
+    const parsedProfile = JSON.parse(text || "{}");
+
+    // Ensure IDs on experience items
+    if (Array.isArray(parsedProfile.experience)) {
+      parsedProfile.experience = parsedProfile.experience.map((exp: any, index: number) => ({
+        ...exp,
+        id: exp.id || `exp_parsed_${Date.now()}_${index}`
+      }));
+    }
+
+    res.json({ success: true, profile: parsedProfile, providerUsed });
+  } catch (error: any) {
+    console.error("Error parsing resume:", error);
+    res.status(500).json({ success: false, error: error.message || "Failed to parse resume" });
+  }
+});
+
 // API 3: Tailor Resume & Calculate Match Score
 app.post("/api/gemini/tailor-resume", async (req, res) => {
   try {